Triple

T16860991
Position Surface form Disambiguated ID Type / Status
Subject Karakoram Highway E409908 entity
Predicate terminusInChina P1866 FINISHED
Object Kashgar E89243 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kashgar | Statement: [Karakoram Highway, terminusInChina, Kashgar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kashgar
Context triple: [Karakoram Highway, terminusInChina, Kashgar]
  • A. Kashgar chosen
    Kashgar is an ancient oasis city in western China’s Xinjiang region that long served as a key cultural and commercial crossroads between East and West.
  • B. Ghulja
    Ghulja is the historical name for Yining, a city in China’s Xinjiang region known as a cultural and commercial center in the Ili River valley.
  • C. Urumqi
    Urumqi is the capital of China’s Xinjiang Uyghur Autonomous Region, known as a major cultural and economic hub in Central Asia and one of the most inland major cities in the world.
  • D. Turpan
    Turpan is an oasis city and depression in China’s Xinjiang region, historically a key Silk Road hub known for its extreme heat, ancient irrigation systems, and grape cultivation.
  • E. Karamay
    Karamay is an oil-rich industrial city in northwestern China known for its major petroleum fields and role in the energy industry of Xinjiang.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b502bc048190baa5a83015407080 completed April 18, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00bb274ba48190951acde0821e05a0 completed May 10, 2026, 5:06 p.m.
Created at: April 10, 2026, 5:24 a.m.